Recovering a Time‐Dependent Diffusion Coefficient From Flux Data in a Fractional Diffusion Model With a Higher‐Order Boundary Condition

ABSTRACT We study an inverse problem for a time‐fractional diffusion equation with a Robin condition at and an eigenparameter‐dependent higher‐order boundary condition at . For the direct problem we prove existence, uniqueness, and regularity of mild solutions. For the inverse recovery of a positive time‐varying coefficient , we introduce a monotone nonlinear operator whose fixed points correspond to data‐consistent coefficients. Monotonicity yields uniqueness, and under mild assumptions the associated fixed‐point (‐) iteration is monotone, bounded, and convergent. A modal discretization with L1 time stepping implements the iteration efficiently. Numerical experiments corroborate the theory and examine robustness to noise and the effect of the fractional order .

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Publication Details

Journal
Mathematical Methods in the Applied Sciences
Published
2026-05-19
DOI
https://doi.org/10.1002/mma.70802
Primary Topic
Fractional Differential Equations Solutions
Type
article
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article

Recovering a Time‐Dependent Diffusion Coefficient From Flux Data in a Fractional Diffusion Model With a Higher‐Order Boundary Condition

Mathematical Methods in the Applied Sciences
Fractional Differential Equations Solutions
article

Recovering a Time‐Dependent Diffusion Coefficient From Flux Data in a Fractional Diffusion Model With a Higher‐Order Boundary Condition

article en

Abstract

ABSTRACT We study an inverse problem for a time‐fractional diffusion equation with a Robin condition at and an eigenparameter‐dependent higher‐order boundary condition at . For the direct problem we prove existence, uniqueness, and regularity of mild solutions. For the inverse recovery of a positive time‐varying coefficient , we introduce a monotone nonlinear operator whose fixed points correspond to data‐consistent coefficients. Monotonicity yields uniqueness, and under mild assumptions the associated fixed‐point (‐) iteration is monotone, bounded, and convergent. A modal discretization with L1 time stepping implements the iteration efficiently. Numerical experiments corroborate the theory and examine robustness to noise and the effect of the fractional order .

Mathematical Methods in the Applied Sciences
Al-Farabi Kazakh National University (KZ), Institute of Mathematics and Mathematical Modeling (KZ)
Reduced inequalities
Openalex Percentile: Top 5%
Fractional Differential Equations Solutions
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